Hybrid Laser/Arc Welding

  • PROCESS DESCRIPTION
    SMU’s Center for Laser Aided Manufacturing (CLAM) has been developing a hybrid laser/arc technology which consists of a 4-kW fiber laser, a 6-axis KUKA robot, and one of the traditional GTAW, GMAW or micro-plasma welding systems. This technology leverages the individual strengths of the laser and arc welding processes in one platform.
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  • ADVANTAGES
     
    Set-up for Hybrid Laser/Arc Welding 

    Deep penetration, high speed, narrow weld bead and HAZ, high quality welds, suppression of humping, reduction of porosities in the weld, possibility to add filler materials, good tolerance to joint fit-up.
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  • CLAM CAPABILITIES
    • Welding of galvanized dual phase steel at gap-free overlap joint configuration
    • Welding of mild steel, aluminum alloys, titanium alloys, stainless steels, and high strength steels
    • Heat treatment via direct diode laser to restore mechanical properties of welded joint in high strength steels
    • Monitoring of the welding process using acoustic emission, airborne sound, and machine vision systems
    • Metallurgical analysis and mechanical testing of welded materials
    • Numerical modeling of the welding process and heat treatment by diode laser
     
     
     Comparison of experimental and numerical results of cross-sectional weld in Laser-GMA hybrid welding
  • Recent Publications
    • F. Kong, J. Ma, R. Kovacevic. Numerical and experimental study of thermally induced residual stresses in the hybrid laser-GMA welding process. The Journal of Materials Processing Technology. 2011, 211 (6): 1102-1111.
    • W. Huang, R. Kovacevic. Development of a real-time laser-based machine vision system to monitor and control welding process, the International Journal of Advanced Manufacturing Technology, DOI:10.10071S00170-012-3902-0,2012.
    • W. Huang, R. Kovacevic. A neutral network and multiple regression method for the characterization of the depth of weld penetration in laser welding based on acoustic signature, the Journal of Intelligent Manufacturing, 2011, 22 (2): 131-143.